Improving on Dijkstra, A* takes into account the direction of your goal. Dr MikePound explains.
Correction: At 8min 38secs 'D' should, of course, be 14 not 12. This does not change the result.
Dijkstra's Algorithm: https://youtu.be/GazC3A4OQTE
How GPSWorks: https://youtu.be/EUrU1y5is3Y
http://www.facebook.com/computerphile
https://twitter.com/computer_phile
This video was filmed and edited by Sean Riley.
Computer Science at the University of Nottingham: http://bit.ly/nottscomputer
Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.com

published:15 Feb 2017

views:395096

Algorithms are the sets of steps necessary to complete computation - they are at the heart of what our devices actually do. And this isn’t a new concept. Since the development of math itself algorithms have been needed to help us complete tasks more efficiently, but today we’re going to take a look a couple modern computing problems like sorting and graph search, and show how we’ve made them more efficient so you can more easily find cheap airfare or map directions to Winterfell... or like a restaurant or something.
Ps. Have you had the chance to play the Grace Hopper game we made in episode 12. Check it out here! http://thoughtcafe.ca/hopper/
CORRECTION:
In the pseudocode for selection sort at 3:09, this line:
swap array items at index and smallest
should be:
swap array items at i and smallest
Produced in collaboration with PBS Digital Studios: http://youtube.com/pbsdigitalstudios
Want to know more about Carrie Anne?
https://about.me/carrieannephilbin
The Latest from PBS Digital Studios: https://www.youtube.com/playlist?list...
Want to find Crash Course elsewhere on the internet?
Facebook - https://www.facebook.com/YouTubeCrash...
Twitter - http://www.twitter.com/TheCrashCourse
Tumblr - http://thecrashcourse.tumblr.com
Support Crash Course on Patreon: http://patreon.com/crashcourse
CC Kids: http://www.youtube.com/crashcoursekids

published:24 May 2017

views:560881

Watch the next lesson:
https://www.khanacademy.org/computing/computer-science/cryptography/crypt/v/intro-to-cryptography?utm_source=YT&utm_medium=Desc&utm_campaign=computerscience
Computer Science on Khan Academy: Learn select topics from computer science - algorithms (how we solve common problems in computer science and measure the efficiency of our solutions), cryptography (how we protect secret information), and information theory (how we encode and compress information).
About Khan Academy: Khan Academy offers practice exercises, instructional videos, and a personalized learning dashboard that empower learners to study at their own pace in and outside of the classroom. We tackle math, science, computer programming, history, art history, economics, and more. Our math missions guide learners from kindergarten to calculus using state-of-the-art, adaptive technology that identifies strengths and learning gaps. We've also partnered with institutions like NASA, The Museum of Modern Art, The California Academy of Sciences, and MIT to offer specialized content.
For free. For everyone. Forever. #YouCanLearnAnything
Subscribe to Khan Academy’s Computer Science channel: https://www.youtube.com/channel/UC8uHgAVBOy5h1fDsjQghWCw?sub_confirmation=1
Subscribe to Khan Academy: https://www.youtube.com/subscription_center?add_user=khanacademy

http://dperrysvendsen.wordpress.com/2014/12/05/pathfinding-algorithms/
This program was originally built to demonstrate the relative efficiency of different pathfinding algorithms in finding the shortest path between two points on a map.
Three algorithms are built in:
• Breadth-first search, an algorithm traditionally used to navigate small, enclosed areas.
• Best-first search, an algorithm generally better suited to more open environments with fewer obstacles.
• A* search, a somewhat more complex algorithm designed to intelligently dodge obstacles.
To represent the map, the program uses a grid of nodes, in which each node has up to four traversable edges: up, down, left and right. One node is designated the root node, and another the target node. In addition, a node can be marked as impassable, effectively creating an obstacle around which an algorithm must navigate.
In order to generate a path, each algorithm utilises an open set, a collection of nodes representing the boundary of an increasing search area. The algorithm gradually expands the search area by evaluating one node at a time from its open set.
Evaluating a node involves first checking if it is the target node – if this is the case, a path has been found and the algorithm terminates. Failing this, the node is removed from the open set and marked as visited so that is will not be re-added (this prevents the algorithm from generating loops). Finally, each of the nodes immediate unvisited neighbours are added to the open set. Crucially, for each of these neighbouring nodes, the current node is marked as their predecessor.
This search area continues to expand until either it reaches the target node (meaning a path was been found), or there are no new nodes to evaluate (meaning no path was found). If a path is found, it is then reconstructed based on the predecessor of each node, starting from the target node, and continuing until the root node is reached.
The difference between each algorithm lies in how they decide the order in which the Nodes in the open set are evaluated.
• Breadth-first search uses a Queue, which functions much like a real-world queue in ensuring that Nodes are evaluated in the same order they were added.
• Best-first search uses a List, assigning each Node a heuristic value based on its estimated distance from the target node, not taking into account any obstacles. This value is simply the rectilinear distance, or the sum of the horizontal and vertical offsets, between the two points. The Node with the lowest heuristic value is then chosen to be evaluated.
• A* search also uses a List, and also assigns each Node a heuristic value. However, it adds this heuristic value to the cumulative cost (the path length) to generate the Node’s f-score. The Node with the lowest f-score is then chosen to be evaluated.

This video will present the (full) process of implementing A* and Dijkstra algorithms in Java, both as efficiently as possible by careful choice of data structures. Plus, I forgot to add *CLOSED.add(currentNode);* right before the inner *for* loop of the pathfinder. Sorry for inconvenience. :-)

published:01 Oct 2016

views:4062

Ex-Google Tech LeadPatrick Shyu gives his top tips on acing the coding interview.
Visithttp://brilliant.org/techlead to learn computer science algorithms and fundamentals. The first 200 get 20% off premium.
Find out the top must-know algorithms for your coding interview, including tree traversals, sorting, data structures, OOP, and more!
Follow me at
http://instagram.com/patrickshyu
http://twitter.com/patrickshyu

published:10 Aug 2018

views:200433

We want to find the shortest path to a destination in grid world.
We have to process many possible paths.
We keep a record of the best path to any grid square we have
processed.
We estimate the cost to the goal from each grid square that we
visit.
We only need to process each grid square once.
We do not need to process all grid squares.

Buy the Book: http://amzn.to/2Gbbrlx
JoinFacebookGroup: https://www.facebook.com/groups/majorprep/
Follow MajorPrep on Twitter: https://twitter.com/MajorPrep1
A huge part of computer science is learning about algorithms and how to apply them. Algorithms can be very simple and very complex and in this video I outline some algorithms with practical applications that you can even apply to your life.
►See More of My FavoriteBooks: https://www.amazon.com/shop/majorprep
***************************************************
► For more information on math, science, and engineering majors, check us out at https://majorprep.com
***************************************************
► Patreon: https://patreon.com/majorprep
► PayPal: https://www.paypal.me/majorprep

Khan Academy

Khan Academy is a non-profit educational organization created in 2006 by educator Salman Khan with the aim of providing a free, world-class education for anyone, anywhere. The organization produces short lectures in the form of YouTube videos. In addition to micro lectures, the organization's website features practice exercises and tools for educators. All resources are available for free to anyone around the world. The main language of the website is English, but the content is also available in other languages.

In late 2004, Khan began tutoring his cousin Nadia who needed help with math using Yahoo!'s Doodle notepad.When other relatives and friends sought similar help, he decided that it would be more practical to distribute the tutorials on YouTube. The videos' popularity and the testimonials of appreciative students prompted Khan to quit his job in finance as a hedge fund analyst at Connective Capital Management in 2009, and focus on the tutorials (then released under the moniker "Khan Academy") full-time.

Computer science

Computer science is the scientific and practical approach to computation and its applications. It is the systematic study of the feasibility, structure, expression, and mechanization of the methodical procedures (or algorithms) that underlie the acquisition, representation, processing, storage, communication of, and access to information. An alternate, more succinct definition of computer science is the study of automating algorithmic processes that scale. A computer scientist specializes in the theory of computation and the design of computational systems.

Information technology

Information technology (IT) is the application of computers and telecommunications equipment to store, retrieve, transmit and manipulate data, often in the context of a business or other enterprise. IT is considered a subset of information and communications technology (ICT). In 2012, Zuppo proposed an ICT hierarchy where each hierarchy level "contain some degree of commonality in that they are related to technologies that facilitate the transfer of information and various types of electronically mediated communications.". Business/IT was one level of the ICT hierarchy.

Humans have been storing, retrieving, manipulating and communicating information since the Sumerians in Mesopotamia developed writing in about 3000BC, but the term information technology in its modern sense first appeared in a 1958 article published in the Harvard Business Review; authors Harold J. Leavitt and Thomas L. Whisler commented that "the new technology does not yet have a single established name. We shall call it information technology (IT)." Their definition consists of three categories: techniques for processing, the application of statistical and mathematical methods to decision-making, and the simulation of higher-order thinking through computer programs.

Computer Science (UIL)

Computer Science is designed to test students' programming abilities. It is not the same as the Computer Applications contest, which tests students' abilities to use word processing, spreadsheet, and database applications software, including integration of applications.

Computer Science began during the 1990-91 scholastic year as strictly a team event. It was not scored as an individual event until the 1996-97 school year.

Eligibility

Each school may send up to four students. However, in districts with eight or more schools the number of students per school may be limited to three. In order for the school to compete in the team competition the school must send three students.

Rules and Scoring

The contest consists of two parts, a written test and a programming exercise.

On the written test, 45 minutes are allotted. No time warnings are given, but at the end of the 45 minutes the student may finish completing an answer. Six points are given for each correct answer; two points are deducted for each incorrect answer. Skipped or unanswered questions are not scored.

Rubik's Cube

Rubik's Cube is a 3-Dcombination puzzle invented in 1974 by Hungarian sculptor and professor of architectureErnő Rubik.
Originally called the Magic Cube, the puzzle was licensed by Rubik to be sold by Ideal Toy Corp. in 1980 via businessman Tibor Laczi and Seven Towns founder Tom Kremer, and won the German Game of the Year special award for Best Puzzle that year. As of January 2009, 350 million cubes had been sold worldwide making it the world's top-selling puzzle game. It is widely considered to be the world's best-selling toy.

In a classic Rubik's Cube, each of the six faces is covered by nine stickers, each of one of six solid colours: white, red, blue, orange, green, and yellow. In currently sold models, white is opposite yellow, blue is opposite green, and orange is opposite red, and the red, white and blue are arranged in that order in a clockwise arrangement. On early cubes, the position of the colours varied from cube to cube. An internal pivot mechanism enables each face to turn independently, thus mixing up the colours. For the puzzle to be solved, each face must be returned to have only one colour.
Similar puzzles have now been produced with various numbers of sides, dimensions, and stickers, not all of them by Rubik.

Crash Course

Plot

Crash Course centers on a group of high schoolers in a driver’s education class; many for the second or third time. The recently divorced teacher, super-passive Larry Pearl, is on thin ice with the football fanatic principal, Principal Paulson, who is being pressured by the district superintendent to raise driver’s education completion rates or lose his coveted football program. With this in mind, Principal Paulson and his assistant, with a secret desire for his job, Abner Frasier, hire an outside driver’s education instructor with a very tough reputation, Edna Savage, aka E.W. Savage, who quickly takes control of the class.

The plot focuses mostly on the students and their interactions with their teachers and each other. In the beginning, Rico is the loner with just a few friends, Chadley is the bookish nerd with few friends who longs to be cool and also longs to be a part of Vanessa’s life who is the young, friendly and attractive girl who had to fake her mother’s signature on her driver’s education permission slip. Kichi is the hip-hop Asian kid who often raps what he has to say and constantly flirts with Maria, the rich foreign girl who thinks that the right-of-way on the roadways always goes to (insert awesomely fake foreign Latino accent) “my father’s limo”. Finally you have stereotypical football meathead J.J., who needs to pass his English exam to keep his eligibility and constantly asks out and gets rejected by Alice, the tomboy whose father owns “Santini & Son” Concrete Company. Alice is portrayed as being the “son” her father wanted.

Crash Course (YouTube)

Crash Course (sometimes stylized as CrashCourse) is an educational YouTube channel started by the Green brothers, Hank Green and John Green, who are notable for their VlogBrothers channel. Originally, John and Hank presented humanities and science courses to viewers, respectively, although the series has since expanded to incorporate courses by additional hosts.

Crash Course was one of the 100 initial channels of YouTube's $100 million original channel initiative. Crash Course launched a preview on December 2, 2011. As of February 14, 2016, the Crash Course YouTube channel has gotten 3,947,842 subscribers and has received over 300 million video views. In November 2014, Hank Green announced that a partnership with PBS Digital Studios would allow them to produce more courses, starting in January 2015.

Currently there are fourteen seasons of Crash Course, with Hank and John each hosting five. Together with Emily Graslie, they co-hosted Big History. As part of the PBS partnership, Phil Plait and Craig Benzine have hosted series about Astronomy and U.S. Government and Politics, respectively. A second channel, Crash Course Kids, is hosted by Sabrina Cruz and has started its first series, Science.

A* (A Star) Search Algorithm - Computerphile

Improving on Dijkstra, A* takes into account the direction of your goal. Dr MikePound explains.
Correction: At 8min 38secs 'D' should, of course, be 14 not 12. This does not change the result.
Dijkstra's Algorithm: https://youtu.be/GazC3A4OQTE
How GPSWorks: https://youtu.be/EUrU1y5is3Y
http://www.facebook.com/computerphile
https://twitter.com/computer_phile
This video was filmed and edited by Sean Riley.
Computer Science at the University of Nottingham: http://bit.ly/nottscomputer
Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.com

11:44

Intro to Algorithms: Crash Course Computer Science #13

Intro to Algorithms: Crash Course Computer Science #13

Intro to Algorithms: Crash Course Computer Science #13

Algorithms are the sets of steps necessary to complete computation - they are at the heart of what our devices actually do. And this isn’t a new concept. Since the development of math itself algorithms have been needed to help us complete tasks more efficiently, but today we’re going to take a look a couple modern computing problems like sorting and graph search, and show how we’ve made them more efficient so you can more easily find cheap airfare or map directions to Winterfell... or like a restaurant or something.
Ps. Have you had the chance to play the Grace Hopper game we made in episode 12. Check it out here! http://thoughtcafe.ca/hopper/
CORRECTION:
In the pseudocode for selection sort at 3:09, this line:
swap array items at index and smallest
should be:
swap array items at i and smallest
Produced in collaboration with PBS Digital Studios: http://youtube.com/pbsdigitalstudios
Want to know more about Carrie Anne?
https://about.me/carrieannephilbin
The Latest from PBS Digital Studios: https://www.youtube.com/playlist?list...
Want to find Crash Course elsewhere on the internet?
Facebook - https://www.facebook.com/YouTubeCrash...
Twitter - http://www.twitter.com/TheCrashCourse
Tumblr - http://thecrashcourse.tumblr.com
Support Crash Course on Patreon: http://patreon.com/crashcourse
CC Kids: http://www.youtube.com/crashcoursekids

5:28

What is an algorithm and why should you care? | Algorithms | Computer Science | Khan Academy

What is an algorithm and why should you care? | Algorithms | Computer Science | Khan Academy

What is an algorithm and why should you care? | Algorithms | Computer Science | Khan Academy

Watch the next lesson:
https://www.khanacademy.org/computing/computer-science/cryptography/crypt/v/intro-to-cryptography?utm_source=YT&utm_medium=Desc&utm_campaign=computerscience
Computer Science on Khan Academy: Learn select topics from computer science - algorithms (how we solve common problems in computer science and measure the efficiency of our solutions), cryptography (how we protect secret information), and information theory (how we encode and compress information).
About Khan Academy: Khan Academy offers practice exercises, instructional videos, and a personalized learning dashboard that empower learners to study at their own pace in and outside of the classroom. We tackle math, science, computer programming, history, art history, economics, and more. Our math missions guide learners from kindergarten to calculus using state-of-the-art, adaptive technology that identifies strengths and learning gaps. We've also partnered with institutions like NASA, The Museum of Modern Art, The California Academy of Sciences, and MIT to offer specialized content.
For free. For everyone. Forever. #YouCanLearnAnything
Subscribe to Khan Academy’s Computer Science channel: https://www.youtube.com/channel/UC8uHgAVBOy5h1fDsjQghWCw?sub_confirmation=1
Subscribe to Khan Academy: https://www.youtube.com/subscription_center?add_user=khanacademy

Pathfinding Algorithms

http://dperrysvendsen.wordpress.com/2014/12/05/pathfinding-algorithms/
This program was originally built to demonstrate the relative efficiency of different pathfinding algorithms in finding the shortest path between two points on a map.
Three algorithms are built in:
• Breadth-first search, an algorithm traditionally used to navigate small, enclosed areas.
• Best-first search, an algorithm generally better suited to more open environments with fewer obstacles.
• A* search, a somewhat more complex algorithm designed to intelligently dodge obstacles.
To represent the map, the program uses a grid of nodes, in which each node has up to four traversable edges: up, down, left and right. One node is designated the root node, and another the target node. In addition, a node can be marked as impassable, effectively creating an obstacle around which an algorithm must navigate.
In order to generate a path, each algorithm utilises an open set, a collection of nodes representing the boundary of an increasing search area. The algorithm gradually expands the search area by evaluating one node at a time from its open set.
Evaluating a node involves first checking if it is the target node – if this is the case, a path has been found and the algorithm terminates. Failing this, the node is removed from the open set and marked as visited so that is will not be re-added (this prevents the algorithm from generating loops). Finally, each of the nodes immediate unvisited neighbours are added to the open set. Crucially, for each of these neighbouring nodes, the current node is marked as their predecessor.
This search area continues to expand until either it reaches the target node (meaning a path was been found), or there are no new nodes to evaluate (meaning no path was found). If a path is found, it is then reconstructed based on the predecessor of each node, starting from the target node, and continuing until the root node is reached.
The difference between each algorithm lies in how they decide the order in which the Nodes in the open set are evaluated.
• Breadth-first search uses a Queue, which functions much like a real-world queue in ensuring that Nodes are evaluated in the same order they were added.
• Best-first search uses a List, assigning each Node a heuristic value based on its estimated distance from the target node, not taking into account any obstacles. This value is simply the rectilinear distance, or the sum of the horizontal and vertical offsets, between the two points. The Node with the lowest heuristic value is then chosen to be evaluated.
• A* search also uses a List, and also assigns each Node a heuristic value. However, it adds this heuristic value to the cumulative cost (the path length) to generate the Node’s f-score. The Node with the lowest f-score is then chosen to be evaluated.

A* and Dijkstra algorithms: full Java video tutorial

This video will present the (full) process of implementing A* and Dijkstra algorithms in Java, both as efficiently as possible by careful choice of data structures. Plus, I forgot to add *CLOSED.add(currentNode);* right before the inner *for* loop of the pathfinder. Sorry for inconvenience. :-)

11:12

Top Algorithms for the Coding Interview (for software engineers)

Top Algorithms for the Coding Interview (for software engineers)

Top Algorithms for the Coding Interview (for software engineers)

Ex-Google Tech LeadPatrick Shyu gives his top tips on acing the coding interview.
Visithttp://brilliant.org/techlead to learn computer science algorithms and fundamentals. The first 200 get 20% off premium.
Find out the top must-know algorithms for your coding interview, including tree traversals, sorting, data structures, OOP, and more!
Follow me at
http://instagram.com/patrickshyu
http://twitter.com/patrickshyu

1:01

Maze Solving Algorithms: The A* Algorithm

Maze Solving Algorithms: The A* Algorithm

Maze Solving Algorithms: The A* Algorithm

We want to find the shortest path to a destination in grid world.
We have to process many possible paths.
We keep a record of the best path to any grid square we have
processed.
We estimate the cost to the goal from each grid square that we
visit.
We only need to process each grid square once.
We do not need to process all grid squares.

Algorithms BBC

The Applications of Algorithms

Buy the Book: http://amzn.to/2Gbbrlx
JoinFacebookGroup: https://www.facebook.com/groups/majorprep/
Follow MajorPrep on Twitter: https://twitter.com/MajorPrep1
A huge part of computer science is learning about algorithms and how to apply them. Algorithms can be very simple and very complex and in this video I outline some algorithms with practical applications that you can even apply to your life.
►See More of My FavoriteBooks: https://www.amazon.com/shop/majorprep
***************************************************
► For more information on math, science, and engineering majors, check us out at https://majorprep.com
***************************************************
► Patreon: https://patreon.com/majorprep
► PayPal: https://www.paypal.me/majorprep

15:24

How algorithms shape our world - Kevin Slavin

How algorithms shape our world - Kevin Slavin

How algorithms shape our world - Kevin Slavin

View full lesson: http://ed.ted.com/lessons/kevin-slavin-how-algorithms-shape-our-world
KevinSlavin argues that we're living in a world designed for -- and increasingly controlled by -- algorithms. In this riveting talk from TEDGlobal, he shows how these complex computer programs determine espionage tactics, stock prices, movie scripts, and architecture. Slavin also warns that we are writing code we can't understand with implications we can't control.
Talk by Kevin Slavin.

20:32

How To Solve A Rubik's Cube Using ONLY 4 ALGORITHMS! | Solve The 3x3x3 Cube!

How To Solve A Rubik's Cube Using ONLY 4 ALGORITHMS! | Solve The 3x3x3 Cube!

How To Solve A Rubik's Cube Using ONLY 4 ALGORITHMS! | Solve The 3x3x3 Cube!

This video shows a tutorial on solving the Rubik's Cube using only 4 algorithms. If you like to have another video showing any other cases you might get that you get confused through solving, just comment about it.
Again, Here are the algorithms:
1: F RU R' U' F'
2: R U R' U R U2 R'
3: R' F R' B2 R F' R' B2 R2
4: F2 U L R' F2 L' RU F2Thanks for watching, SUBSCRIBE!!!

A* (A Star) Search Algorithm - Computerphile

Improving on Dijkstra, A* takes into account the direction of your goal. Dr MikePound explains.
Correction: At 8min 38secs 'D' should, of course, be 14 not 12. This does not change the result.
Dijkstra's Algorithm: https://youtu.be/GazC3A4OQTE
How GPSWorks: https://youtu.be/EUrU1y5is3Y
http://www.facebook.com/computerphile
https://twitter.com/computer_phile
This video was filmed and edited by Sean Riley.
Computer Science at the University of Nottingham: http://bit.ly/nottscomputer
Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.com

published: 15 Feb 2017

Intro to Algorithms: Crash Course Computer Science #13

Algorithms are the sets of steps necessary to complete computation - they are at the heart of what our devices actually do. And this isn’t a new concept. Since the development of math itself algorithms have been needed to help us complete tasks more efficiently, but today we’re going to take a look a couple modern computing problems like sorting and graph search, and show how we’ve made them more efficient so you can more easily find cheap airfare or map directions to Winterfell... or like a restaurant or something.
Ps. Have you had the chance to play the Grace Hopper game we made in episode 12. Check it out here! http://thoughtcafe.ca/hopper/
CORRECTION:
In the pseudocode for selection sort at 3:09, this line:
swap array items at index and smallest
should be:
swap array items at i...

published: 24 May 2017

What is an algorithm and why should you care? | Algorithms | Computer Science | Khan Academy

Pathfinding Algorithms

http://dperrysvendsen.wordpress.com/2014/12/05/pathfinding-algorithms/
This program was originally built to demonstrate the relative efficiency of different pathfinding algorithms in finding the shortest path between two points on a map.
Three algorithms are built in:
• Breadth-first search, an algorithm traditionally used to navigate small, enclosed areas.
• Best-first search, an algorithm generally better suited to more open environments with fewer obstacles.
• A* search, a somewhat more complex algorithm designed to intelligently dodge obstacles.
To represent the map, the program uses a grid of nodes, in which each node has up to four traversable edges: up, down, left and right. One node is designated the root node, and another the target node. In addition, a node can be marked as im...

A* and Dijkstra algorithms: full Java video tutorial

This video will present the (full) process of implementing A* and Dijkstra algorithms in Java, both as efficiently as possible by careful choice of data structures. Plus, I forgot to add *CLOSED.add(currentNode);* right before the inner *for* loop of the pathfinder. Sorry for inconvenience. :-)

published: 01 Oct 2016

Top Algorithms for the Coding Interview (for software engineers)

Ex-Google Tech LeadPatrick Shyu gives his top tips on acing the coding interview.
Visithttp://brilliant.org/techlead to learn computer science algorithms and fundamentals. The first 200 get 20% off premium.
Find out the top must-know algorithms for your coding interview, including tree traversals, sorting, data structures, OOP, and more!
Follow me at
http://instagram.com/patrickshyu
http://twitter.com/patrickshyu

published: 10 Aug 2018

Maze Solving Algorithms: The A* Algorithm

We want to find the shortest path to a destination in grid world.
We have to process many possible paths.
We keep a record of the best path to any grid square we have
processed.
We estimate the cost to the goal from each grid square that we
visit.
We only need to process each grid square once.
We do not need to process all grid squares.

Algorithms BBC

The Applications of Algorithms

Buy the Book: http://amzn.to/2Gbbrlx
JoinFacebookGroup: https://www.facebook.com/groups/majorprep/
Follow MajorPrep on Twitter: https://twitter.com/MajorPrep1
A huge part of computer science is learning about algorithms and how to apply them. Algorithms can be very simple and very complex and in this video I outline some algorithms with practical applications that you can even apply to your life.
►See More of My FavoriteBooks: https://www.amazon.com/shop/majorprep
***************************************************
► For more information on math, science, and engineering majors, check us out at https://majorprep.com
***************************************************
► Patreon: https://patreon.com/majorprep
► PayPal: https://www.paypal.me/majorprep

published: 22 Mar 2018

How algorithms shape our world - Kevin Slavin

View full lesson: http://ed.ted.com/lessons/kevin-slavin-how-algorithms-shape-our-world
KevinSlavin argues that we're living in a world designed for -- and increasingly controlled by -- algorithms. In this riveting talk from TEDGlobal, he shows how these complex computer programs determine espionage tactics, stock prices, movie scripts, and architecture. Slavin also warns that we are writing code we can't understand with implications we can't control.
Talk by Kevin Slavin.

published: 25 Nov 2012

How To Solve A Rubik's Cube Using ONLY 4 ALGORITHMS! | Solve The 3x3x3 Cube!

This video shows a tutorial on solving the Rubik's Cube using only 4 algorithms. If you like to have another video showing any other cases you might get that you get confused through solving, just comment about it.
Again, Here are the algorithms:
1: F RU R' U' F'
2: R U R' U R U2 R'
3: R' F R' B2 R F' R' B2 R2
4: F2 U L R' F2 L' RU F2Thanks for watching, SUBSCRIBE!!!

Improving on Dijkstra, A* takes into account the direction of your goal. Dr MikePound explains.
Correction: At 8min 38secs 'D' should, of course, be 14 not 12. This does not change the result.
Dijkstra's Algorithm: https://youtu.be/GazC3A4OQTE
How GPSWorks: https://youtu.be/EUrU1y5is3Y
http://www.facebook.com/computerphile
https://twitter.com/computer_phile
This video was filmed and edited by Sean Riley.
Computer Science at the University of Nottingham: http://bit.ly/nottscomputer
Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.com

Improving on Dijkstra, A* takes into account the direction of your goal. Dr MikePound explains.
Correction: At 8min 38secs 'D' should, of course, be 14 not 12. This does not change the result.
Dijkstra's Algorithm: https://youtu.be/GazC3A4OQTE
How GPSWorks: https://youtu.be/EUrU1y5is3Y
http://www.facebook.com/computerphile
https://twitter.com/computer_phile
This video was filmed and edited by Sean Riley.
Computer Science at the University of Nottingham: http://bit.ly/nottscomputer
Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.com

Intro to Algorithms: Crash Course Computer Science #13

Algorithms are the sets of steps necessary to complete computation - they are at the heart of what our devices actually do. And this isn’t a new concept. Since ...

Algorithms are the sets of steps necessary to complete computation - they are at the heart of what our devices actually do. And this isn’t a new concept. Since the development of math itself algorithms have been needed to help us complete tasks more efficiently, but today we’re going to take a look a couple modern computing problems like sorting and graph search, and show how we’ve made them more efficient so you can more easily find cheap airfare or map directions to Winterfell... or like a restaurant or something.
Ps. Have you had the chance to play the Grace Hopper game we made in episode 12. Check it out here! http://thoughtcafe.ca/hopper/
CORRECTION:
In the pseudocode for selection sort at 3:09, this line:
swap array items at index and smallest
should be:
swap array items at i and smallest
Produced in collaboration with PBS Digital Studios: http://youtube.com/pbsdigitalstudios
Want to know more about Carrie Anne?
https://about.me/carrieannephilbin
The Latest from PBS Digital Studios: https://www.youtube.com/playlist?list...
Want to find Crash Course elsewhere on the internet?
Facebook - https://www.facebook.com/YouTubeCrash...
Twitter - http://www.twitter.com/TheCrashCourse
Tumblr - http://thecrashcourse.tumblr.com
Support Crash Course on Patreon: http://patreon.com/crashcourse
CC Kids: http://www.youtube.com/crashcoursekids

Algorithms are the sets of steps necessary to complete computation - they are at the heart of what our devices actually do. And this isn’t a new concept. Since the development of math itself algorithms have been needed to help us complete tasks more efficiently, but today we’re going to take a look a couple modern computing problems like sorting and graph search, and show how we’ve made them more efficient so you can more easily find cheap airfare or map directions to Winterfell... or like a restaurant or something.
Ps. Have you had the chance to play the Grace Hopper game we made in episode 12. Check it out here! http://thoughtcafe.ca/hopper/
CORRECTION:
In the pseudocode for selection sort at 3:09, this line:
swap array items at index and smallest
should be:
swap array items at i and smallest
Produced in collaboration with PBS Digital Studios: http://youtube.com/pbsdigitalstudios
Want to know more about Carrie Anne?
https://about.me/carrieannephilbin
The Latest from PBS Digital Studios: https://www.youtube.com/playlist?list...
Want to find Crash Course elsewhere on the internet?
Facebook - https://www.facebook.com/YouTubeCrash...
Twitter - http://www.twitter.com/TheCrashCourse
Tumblr - http://thecrashcourse.tumblr.com
Support Crash Course on Patreon: http://patreon.com/crashcourse
CC Kids: http://www.youtube.com/crashcoursekids

Pathfinding Algorithms

http://dperrysvendsen.wordpress.com/2014/12/05/pathfinding-algorithms/
This program was originally built to demonstrate the relative efficiency of different pa...

http://dperrysvendsen.wordpress.com/2014/12/05/pathfinding-algorithms/
This program was originally built to demonstrate the relative efficiency of different pathfinding algorithms in finding the shortest path between two points on a map.
Three algorithms are built in:
• Breadth-first search, an algorithm traditionally used to navigate small, enclosed areas.
• Best-first search, an algorithm generally better suited to more open environments with fewer obstacles.
• A* search, a somewhat more complex algorithm designed to intelligently dodge obstacles.
To represent the map, the program uses a grid of nodes, in which each node has up to four traversable edges: up, down, left and right. One node is designated the root node, and another the target node. In addition, a node can be marked as impassable, effectively creating an obstacle around which an algorithm must navigate.
In order to generate a path, each algorithm utilises an open set, a collection of nodes representing the boundary of an increasing search area. The algorithm gradually expands the search area by evaluating one node at a time from its open set.
Evaluating a node involves first checking if it is the target node – if this is the case, a path has been found and the algorithm terminates. Failing this, the node is removed from the open set and marked as visited so that is will not be re-added (this prevents the algorithm from generating loops). Finally, each of the nodes immediate unvisited neighbours are added to the open set. Crucially, for each of these neighbouring nodes, the current node is marked as their predecessor.
This search area continues to expand until either it reaches the target node (meaning a path was been found), or there are no new nodes to evaluate (meaning no path was found). If a path is found, it is then reconstructed based on the predecessor of each node, starting from the target node, and continuing until the root node is reached.
The difference between each algorithm lies in how they decide the order in which the Nodes in the open set are evaluated.
• Breadth-first search uses a Queue, which functions much like a real-world queue in ensuring that Nodes are evaluated in the same order they were added.
• Best-first search uses a List, assigning each Node a heuristic value based on its estimated distance from the target node, not taking into account any obstacles. This value is simply the rectilinear distance, or the sum of the horizontal and vertical offsets, between the two points. The Node with the lowest heuristic value is then chosen to be evaluated.
• A* search also uses a List, and also assigns each Node a heuristic value. However, it adds this heuristic value to the cumulative cost (the path length) to generate the Node’s f-score. The Node with the lowest f-score is then chosen to be evaluated.

http://dperrysvendsen.wordpress.com/2014/12/05/pathfinding-algorithms/
This program was originally built to demonstrate the relative efficiency of different pathfinding algorithms in finding the shortest path between two points on a map.
Three algorithms are built in:
• Breadth-first search, an algorithm traditionally used to navigate small, enclosed areas.
• Best-first search, an algorithm generally better suited to more open environments with fewer obstacles.
• A* search, a somewhat more complex algorithm designed to intelligently dodge obstacles.
To represent the map, the program uses a grid of nodes, in which each node has up to four traversable edges: up, down, left and right. One node is designated the root node, and another the target node. In addition, a node can be marked as impassable, effectively creating an obstacle around which an algorithm must navigate.
In order to generate a path, each algorithm utilises an open set, a collection of nodes representing the boundary of an increasing search area. The algorithm gradually expands the search area by evaluating one node at a time from its open set.
Evaluating a node involves first checking if it is the target node – if this is the case, a path has been found and the algorithm terminates. Failing this, the node is removed from the open set and marked as visited so that is will not be re-added (this prevents the algorithm from generating loops). Finally, each of the nodes immediate unvisited neighbours are added to the open set. Crucially, for each of these neighbouring nodes, the current node is marked as their predecessor.
This search area continues to expand until either it reaches the target node (meaning a path was been found), or there are no new nodes to evaluate (meaning no path was found). If a path is found, it is then reconstructed based on the predecessor of each node, starting from the target node, and continuing until the root node is reached.
The difference between each algorithm lies in how they decide the order in which the Nodes in the open set are evaluated.
• Breadth-first search uses a Queue, which functions much like a real-world queue in ensuring that Nodes are evaluated in the same order they were added.
• Best-first search uses a List, assigning each Node a heuristic value based on its estimated distance from the target node, not taking into account any obstacles. This value is simply the rectilinear distance, or the sum of the horizontal and vertical offsets, between the two points. The Node with the lowest heuristic value is then chosen to be evaluated.
• A* search also uses a List, and also assigns each Node a heuristic value. However, it adds this heuristic value to the cumulative cost (the path length) to generate the Node’s f-score. The Node with the lowest f-score is then chosen to be evaluated.

A* and Dijkstra algorithms: full Java video tutorial

This video will present the (full) process of implementing A* and Dijkstra algorithms in Java, both as efficiently as possible by careful choice of data structu...

This video will present the (full) process of implementing A* and Dijkstra algorithms in Java, both as efficiently as possible by careful choice of data structures. Plus, I forgot to add *CLOSED.add(currentNode);* right before the inner *for* loop of the pathfinder. Sorry for inconvenience. :-)

This video will present the (full) process of implementing A* and Dijkstra algorithms in Java, both as efficiently as possible by careful choice of data structures. Plus, I forgot to add *CLOSED.add(currentNode);* right before the inner *for* loop of the pathfinder. Sorry for inconvenience. :-)

Ex-Google Tech LeadPatrick Shyu gives his top tips on acing the coding interview.
Visithttp://brilliant.org/techlead to learn computer science algorithms and fundamentals. The first 200 get 20% off premium.
Find out the top must-know algorithms for your coding interview, including tree traversals, sorting, data structures, OOP, and more!
Follow me at
http://instagram.com/patrickshyu
http://twitter.com/patrickshyu

Ex-Google Tech LeadPatrick Shyu gives his top tips on acing the coding interview.
Visithttp://brilliant.org/techlead to learn computer science algorithms and fundamentals. The first 200 get 20% off premium.
Find out the top must-know algorithms for your coding interview, including tree traversals, sorting, data structures, OOP, and more!
Follow me at
http://instagram.com/patrickshyu
http://twitter.com/patrickshyu

Maze Solving Algorithms: The A* Algorithm

We want to find the shortest path to a destination in grid world.
We have to process many possible paths.
We keep a record of the best path to any grid square w...

We want to find the shortest path to a destination in grid world.
We have to process many possible paths.
We keep a record of the best path to any grid square we have
processed.
We estimate the cost to the goal from each grid square that we
visit.
We only need to process each grid square once.
We do not need to process all grid squares.

We want to find the shortest path to a destination in grid world.
We have to process many possible paths.
We keep a record of the best path to any grid square we have
processed.
We estimate the cost to the goal from each grid square that we
visit.
We only need to process each grid square once.
We do not need to process all grid squares.

Buy the Book: http://amzn.to/2Gbbrlx
JoinFacebookGroup: https://www.facebook.com/groups/majorprep/
Follow MajorPrep on Twitter: https://twitter.com/MajorPrep1
A huge part of computer science is learning about algorithms and how to apply them. Algorithms can be very simple and very complex and in this video I outline some algorithms with practical applications that you can even apply to your life.
►See More of My FavoriteBooks: https://www.amazon.com/shop/majorprep
***************************************************
► For more information on math, science, and engineering majors, check us out at https://majorprep.com
***************************************************
► Patreon: https://patreon.com/majorprep
► PayPal: https://www.paypal.me/majorprep

Buy the Book: http://amzn.to/2Gbbrlx
JoinFacebookGroup: https://www.facebook.com/groups/majorprep/
Follow MajorPrep on Twitter: https://twitter.com/MajorPrep1
A huge part of computer science is learning about algorithms and how to apply them. Algorithms can be very simple and very complex and in this video I outline some algorithms with practical applications that you can even apply to your life.
►See More of My FavoriteBooks: https://www.amazon.com/shop/majorprep
***************************************************
► For more information on math, science, and engineering majors, check us out at https://majorprep.com
***************************************************
► Patreon: https://patreon.com/majorprep
► PayPal: https://www.paypal.me/majorprep

How algorithms shape our world - Kevin Slavin

View full lesson: http://ed.ted.com/lessons/kevin-slavin-how-algorithms-shape-our-world
KevinSlavin argues that we're living in a world designed for -- and in...

View full lesson: http://ed.ted.com/lessons/kevin-slavin-how-algorithms-shape-our-world
KevinSlavin argues that we're living in a world designed for -- and increasingly controlled by -- algorithms. In this riveting talk from TEDGlobal, he shows how these complex computer programs determine espionage tactics, stock prices, movie scripts, and architecture. Slavin also warns that we are writing code we can't understand with implications we can't control.
Talk by Kevin Slavin.

View full lesson: http://ed.ted.com/lessons/kevin-slavin-how-algorithms-shape-our-world
KevinSlavin argues that we're living in a world designed for -- and increasingly controlled by -- algorithms. In this riveting talk from TEDGlobal, he shows how these complex computer programs determine espionage tactics, stock prices, movie scripts, and architecture. Slavin also warns that we are writing code we can't understand with implications we can't control.
Talk by Kevin Slavin.

A* (A Star) Search Algorithm - Computerphile

Improving on Dijkstra, A* takes into account the direction of your goal. Dr MikePound explains.
Correction: At 8min 38secs 'D' should, of course, be 14 not 12. This does not change the result.
Dijkstra's Algorithm: https://youtu.be/GazC3A4OQTE
How GPSWorks: https://youtu.be/EUrU1y5is3Y
http://www.facebook.com/computerphile
https://twitter.com/computer_phile
This video was filmed and edited by Sean Riley.
Computer Science at the University of Nottingham: http://bit.ly/nottscomputer
Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.com

Intro to Algorithms: Crash Course Computer Science #13

Algorithms are the sets of steps necessary to complete computation - they are at the heart of what our devices actually do. And this isn’t a new concept. Since the development of math itself algorithms have been needed to help us complete tasks more efficiently, but today we’re going to take a look a couple modern computing problems like sorting and graph search, and show how we’ve made them more efficient so you can more easily find cheap airfare or map directions to Winterfell... or like a restaurant or something.
Ps. Have you had the chance to play the Grace Hopper game we made in episode 12. Check it out here! http://thoughtcafe.ca/hopper/
CORRECTION:
In the pseudocode for selection sort at 3:09, this line:
swap array items at index and smallest
should be:
swap array items at i and smallest
Produced in collaboration with PBS Digital Studios: http://youtube.com/pbsdigitalstudios
Want to know more about Carrie Anne?
https://about.me/carrieannephilbin
The Latest from PBS Digital Studios: https://www.youtube.com/playlist?list...
Want to find Crash Course elsewhere on the internet?
Facebook - https://www.facebook.com/YouTubeCrash...
Twitter - http://www.twitter.com/TheCrashCourse
Tumblr - http://thecrashcourse.tumblr.com
Support Crash Course on Patreon: http://patreon.com/crashcourse
CC Kids: http://www.youtube.com/crashcoursekids

Pathfinding Algorithms

http://dperrysvendsen.wordpress.com/2014/12/05/pathfinding-algorithms/
This program was originally built to demonstrate the relative efficiency of different pathfinding algorithms in finding the shortest path between two points on a map.
Three algorithms are built in:
• Breadth-first search, an algorithm traditionally used to navigate small, enclosed areas.
• Best-first search, an algorithm generally better suited to more open environments with fewer obstacles.
• A* search, a somewhat more complex algorithm designed to intelligently dodge obstacles.
To represent the map, the program uses a grid of nodes, in which each node has up to four traversable edges: up, down, left and right. One node is designated the root node, and another the target node. In addition, a node can be marked as impassable, effectively creating an obstacle around which an algorithm must navigate.
In order to generate a path, each algorithm utilises an open set, a collection of nodes representing the boundary of an increasing search area. The algorithm gradually expands the search area by evaluating one node at a time from its open set.
Evaluating a node involves first checking if it is the target node – if this is the case, a path has been found and the algorithm terminates. Failing this, the node is removed from the open set and marked as visited so that is will not be re-added (this prevents the algorithm from generating loops). Finally, each of the nodes immediate unvisited neighbours are added to the open set. Crucially, for each of these neighbouring nodes, the current node is marked as their predecessor.
This search area continues to expand until either it reaches the target node (meaning a path was been found), or there are no new nodes to evaluate (meaning no path was found). If a path is found, it is then reconstructed based on the predecessor of each node, starting from the target node, and continuing until the root node is reached.
The difference between each algorithm lies in how they decide the order in which the Nodes in the open set are evaluated.
• Breadth-first search uses a Queue, which functions much like a real-world queue in ensuring that Nodes are evaluated in the same order they were added.
• Best-first search uses a List, assigning each Node a heuristic value based on its estimated distance from the target node, not taking into account any obstacles. This value is simply the rectilinear distance, or the sum of the horizontal and vertical offsets, between the two points. The Node with the lowest heuristic value is then chosen to be evaluated.
• A* search also uses a List, and also assigns each Node a heuristic value. However, it adds this heuristic value to the cumulative cost (the path length) to generate the Node’s f-score. The Node with the lowest f-score is then chosen to be evaluated.

A* and Dijkstra algorithms: full Java video tutorial

This video will present the (full) process of implementing A* and Dijkstra algorithms in Java, both as efficiently as possible by careful choice of data structures. Plus, I forgot to add *CLOSED.add(currentNode);* right before the inner *for* loop of the pathfinder. Sorry for inconvenience. :-)

Top Algorithms for the Coding Interview (for software engineers)

Ex-Google Tech LeadPatrick Shyu gives his top tips on acing the coding interview.
Visithttp://brilliant.org/techlead to learn computer science algorithms and fundamentals. The first 200 get 20% off premium.
Find out the top must-know algorithms for your coding interview, including tree traversals, sorting, data structures, OOP, and more!
Follow me at
http://instagram.com/patrickshyu
http://twitter.com/patrickshyu

Maze Solving Algorithms: The A* Algorithm

We want to find the shortest path to a destination in grid world.
We have to process many possible paths.
We keep a record of the best path to any grid square we have
processed.
We estimate the cost to the goal from each grid square that we
visit.
We only need to process each grid square once.
We do not need to process all grid squares.

The Applications of Algorithms

Buy the Book: http://amzn.to/2Gbbrlx
JoinFacebookGroup: https://www.facebook.com/groups/majorprep/
Follow MajorPrep on Twitter: https://twitter.com/MajorPrep1
A huge part of computer science is learning about algorithms and how to apply them. Algorithms can be very simple and very complex and in this video I outline some algorithms with practical applications that you can even apply to your life.
►See More of My FavoriteBooks: https://www.amazon.com/shop/majorprep
***************************************************
► For more information on math, science, and engineering majors, check us out at https://majorprep.com
***************************************************
► Patreon: https://patreon.com/majorprep
► PayPal: https://www.paypal.me/majorprep

How algorithms shape our world - Kevin Slavin

View full lesson: http://ed.ted.com/lessons/kevin-slavin-how-algorithms-shape-our-world
KevinSlavin argues that we're living in a world designed for -- and increasingly controlled by -- algorithms. In this riveting talk from TEDGlobal, he shows how these complex computer programs determine espionage tactics, stock prices, movie scripts, and architecture. Slavin also warns that we are writing code we can't understand with implications we can't control.
Talk by Kevin Slavin.

Khan Academy

Khan Academy is a non-profit educational organization created in 2006 by educator Salman Khan with the aim of providing a free, world-class education for anyone, anywhere. The organization produces short lectures in the form of YouTube videos. In addition to micro lectures, the organization's website features practice exercises and tools for educators. All resources are available for free to anyone around the world. The main language of the website is English, but the content is also available in other languages.

In late 2004, Khan began tutoring his cousin Nadia who needed help with math using Yahoo!'s Doodle notepad.When other relatives and friends sought similar help, he decided that it would be more practical to distribute the tutorials on YouTube. The videos' popularity and the testimonials of appreciative students prompted Khan to quit his job in finance as a hedge fund analyst at Connective Capital Management in 2009, and focus on the tutorials (then released under the moniker "Khan Academy") full-time.

The solution automatically considers the right business context, picks the appropriate algorithm, factors in ... A single solution with strong data management capabilities, out-of-the-box algorithms and easy-to-use interfaces make it a compelling solution for digital-age retail....

dryriver writes ... The product's short demo reel is here with a few examples ... The fact that the algorithms are realtime capable also means that they may already be being used for live television broadcasts without anyone noticing, particularly in HD and 4K resolution broadcasts ... Read more of this story at Slashdot. ....

I am not saying that photos of Pol Pot are good and selfies are bad. I am saying that the one reveals a subject and the other reveals an algorithm, and that when everything in our society is driven and sustained in existence by the latter, it is all over. ↩︎ The Point. ViewPost → ... ....

How algorithms shape our world - Kevin Slavin...

How To Solve A Rubik's Cube Using ONLY 4 ALGORITHM...

Latest News for: a algorithms

The solution automatically considers the right business context, picks the appropriate algorithm, factors in ... A single solution with strong data management capabilities, out-of-the-box algorithms and easy-to-use interfaces make it a compelling solution for digital-age retail....

dryriver writes ... The product's short demo reel is here with a few examples ... The fact that the algorithms are realtime capable also means that they may already be being used for live television broadcasts without anyone noticing, particularly in HD and 4K resolution broadcasts ... Read more of this story at Slashdot. ....

I am not saying that photos of Pol Pot are good and selfies are bad. I am saying that the one reveals a subject and the other reveals an algorithm, and that when everything in our society is driven and sustained in existence by the latter, it is all over. ↩︎ The Point. ViewPost → ... ....

Reporting about large-scale finance decisions is difficult for any journalist—but a team of German investigative reporters has crowdsourced a major investigative story revealing flaws in a closely guarded credit scoring algorithm. Most citizens in Germany have a Schufa score, which is something like the FICO score in the US ... ....

Some members of the financial old-guard simply “personally find algorithms confusing.” Levine, a former investment banker himself, has little sympathy ... The funny thing is, we’ve always been quite bad at knowing how to attribute market volatility, which long predates algorithm trading....

Qyresearchreports include new market research report GlobalAlgorithmic Trading Market Size, Status and Forecast 2018-2025 to its huge collection of research reports. This report focuses on the global Algorithmic Trading status, future forecast, growth opportunity, key market and key players ... are now the key developers of Algorithmic Trading....